Journal of radiological science and technology (대한방사선기술학회지:방사선기술과학)

Korean Society of Radiological Science (대한방사선과학회)
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Feasibility on Statistical Process Control Analysis of Delivery Quality Assurance in Helical Tomotherapy

토모테라피에서 선량품질보증 분석을 위한 통계적공정관리의 타당성

  • 장경환 (극동대학교 방사선학과)
  • Received : 2022.09.01
  • Accepted : 2022.11.28
  • Published : 2022.12.31
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Abstract

The purpose of this study was to retrospectively investigate the upper and lower control limits of treatment planning parameters using EBT film based delivery quality assurance (DQA) results and to analyze the results of statistical process control (SPC) in helical tomotherapy (HT). A total of 152 patients who passed or failed DQA results were retrospectively included in this study. Prostate (n = 66), rectal (n = 51), and large-field cancer patients, including lymph nodes (n = 35), were randomly selected. The absolute point dose difference (DD) and global gamma passing rate (GPR) were analyzed for all patients. Control charts were used to evaluate the upper and lower control limits (UCL and LCL) for all the assessed treatment planning parameters. Treatment planning parameters such as gantry period, leaf open time (LOT), pitch, field width, actual and planning modulation factor, treatment time, couch speed, and couch travel were analyzed to provide the optimal range using the DQA results. The classification and regression tree (CART) was used to predict the relative importance of variables in the DQA results from various treatment planning parameters. We confirmed that the proportion of patients with an LOT below 100 ms in the failure group was relatively higher than that in the passing group. SPC can detect QA failure prior to over dosimetric QA tolerance levels. The acceptable tolerance range of each planning parameter may assist in the prediction of DQA failures using the SPC tool in the future.

Keywords

Acknowledgement

The author gratefully thank Professor Jin Sung Kim and Professor Chae-Seon Hong (Department of Radiation Oncology, Yonsei University College of Medicine) for their valuable advices and support on this study. This results was suportedby "Regional InovationStrategy (RIS)" through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE) (2022RIS-001(1345341783))

References

  1. Miften M, Olch A, Mihailidis D, Moran J, Pawlicki T, Molineu A, et al. Tolerance limits and methodologies for IMRT measurement-based verification QA: Recommendations of AAPM Task Group No. 218. Med Phys. 2018;45(4):e53-83.  https://doi.org/10.1002/mp.12810
  2. Intensity Modulated Radiation Therapy Collaborative Working Group: Intensity-modulated radiotherapy: Current status and issues of interest. Int J Radiat Oncol Biol Phys. 2001;51(4):880914. 
  3. Cho B. Intensity-modulated radiation therapy: A review with a physics perspective. Radiat Oncol J. 2018;36(1):1-10.  https://doi.org/10.3857/roj.2018.00122
  4. Chang KH, Lee S, Jung H, Choo YW, Cao YJ, Shim JB, et al. Development of a 3D optical scanner for evaluating patient-specific dose distributions. Phys Med. 2015;31(5):553-9.  https://doi.org/10.1016/j.ejmp.2015.05.009
  5. Thiyagarajan R, Nambiraj A, Sinha SN, Yadav G, Kumar A, Subramani V, et al. Analyzing the performance of ArcCHECK diode array detector for VMAT plan. Rep Pract Oncol Radiother. 2016;21(1):50-6.  https://doi.org/10.1016/j.rpor.2015.10.004
  6. Chang KH. Treatment Planning Guideline of EBT Film-based Delivery Quality Assurance Using Statistical Process Control in Helical Tomotherapy. Journal of Radiological Science and Technology. 2022;45(5):439-48.  https://doi.org/10.17946/JRST.2022.45.5.439
  7. TomoTherapy Incorporated. TomoTherapy® Treatment System StatRTTM Guide. 2010;(177). 
  8. Cheong KH. Use of Statistical Process Control for Quality Assurance in Radiation Therapy. Prog Med Phys. 2015;26(2):59-71.  https://doi.org/10.14316/pmp.2015.26.2.59
  9. Wheeler DJ, Chambers DS. Understanding statistical process control. 2nd ed. Knoxville, TN: SPC Press; 1992. 
  10. Montgomery DC. Statistical quality control. New York: Wiley; 2009. 
  11. Prins J. Process or product monitoring and control. NIST/SEMATECH e-Handbook of Statistical Methods: National Institute of Standards & Technology, Gaithersburg; 2007. 
  12. Breen SL, Moseley DJ, Zhang B, Sharpe MB. Statistical process control for IMRT dosimetric verification. Med Phys. 2008;35(10):4417-25.  https://doi.org/10.1118/1.2975144
  13. Binny D, Aland T, Archibald-Heeren BR, Trapp JV, Kairn T, Crowe SB. A multi-institutional evaluation of machine performance check system on treatment beam output and symmetry using statistical process control. J Appl Clin Med Phys. 2019;20(3):71-80.  https://doi.org/10.1002/acm2.12547
  14. Binny D, Lancaster CM, Byrne M, Kairn T, Trapp JV, Crowe SB. Tomotherapy treatment site specific planning using statistical process control. Phys Med. 2018;53:32-9.  https://doi.org/10.1016/j.ejmp.2018.08.003
  15. Mezzenga E, D'Errico V, Sarnelli A, Strigari L, Menghi E, Marcocci F, et al. Preliminary Retrospective Analysis of Daily Tomotherapy Output Constancy Checks Using Statistical Process Control. PLoS One. 2016;11(2):e0147936. 
  16. Meyers SM, Balderson MJ, Letourneau D. Evaluation of Elekta Agility multi-leaf collimator performance using statistical process control tools. J Appl Clin Med Phys. 2019;20(7):100-8.  https://doi.org/10.1002/acm2.12660
  17. Sanghangthum T, Suriyapee S, Srisatit S, Pawlicki T. Statistical process control analysis for patient-specific IMRT and VMAT QA. J Radiat Res. 2013;54(3):546-52.  https://doi.org/10.1093/jrr/rrs112
  18. Chang KH, Lee YH, Park BH, Han MC, Kim J, et al. Statistical Analysis of Treatment Planning Parameters for Prediction of Delivery Quality Assurance Failure for Helical Tomotherapy. Technol Cancer Res Treat. 2020;19:1-9. 
  19. Chang KH, Kim DW, Choi JH, Shin HB, Hong CS, Jung DM, et al. Dosimetric Comparison of Four Commercial Patient-Specific Quality Assurance Devices for Helical Tomotherapy. J Korean Phys Soc. 2020;76(3):257-63.  https://doi.org/10.3938/jkps.76.257
  20. Razali NM, Wah YB. Power comparison of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. J Stat Mod Analyt. 2011;2(1):21-33. 
  21. Thomas SJ, Geater AR. Implications of leaf fluence opening factors on transfer of plans between matched helical tomotherapy machines. Biomed Phys Eng Express. 2017;4(1):017001. 
  22. Vaden R, Schauer N. Efficient planning for efficient treatments on tomotherapy. ASTRO; 2016. 
  23. Westerly DC, Soisson E, Chen Q, Woch K, Schubert L, Olivera G, et al. Treatment planning to improve delivery accuracy and patient throughput in helical tomotherapy. Int J Radiat Oncol Biol Phys. 2009;74(4):1290-7.  https://doi.org/10.1016/j.ijrobp.2009.02.004
  24. Martisikova M, Ackermann B, Jakel O. Analysis of uncertainties in Gafchromic EBT film dosimetry of photon beams. Phys Med Biol. 2008;53(24):7013-27. https://doi.org/10.1088/0031-9155/53/24/001